{smcl}
{* 22Jan2007}{...}
{cmd:help ngreg}
{hline}

{title:Title}

{p2colset 9 20 22 2}{...}
{p2col :{hi:ngtreg} {hline 2}}Grouped dyadic regression{p_end}
{p2colreset}{...}


{title:Syntax}

{p 8 16 2}
{cmd:ngreg} [{depvar} {varlist}] {ifin} {cmd:,} {opt i:d(var1 var2)} [{opt g:roup(varlist)} {opt log:it} {opt noc:onstant} {opt sym:metric}]


{title:Description}

{pstd}
{cmd:ngreg} does either linear or logistic estimation for grouped dyadic data.



{dlgtab:Main}

{phang}
{opt id(var1 var2)} specifies {it:i} and {it:j}.


{phang}
{opt group(varlist)} if specified, varlist defines data grouping.

{phang}
{opt logit} specifies that logistic regression model do be estimated instead of default ordinary least squares.

{phang}
{opt noconstant} suppresses the constant term (intercept) in the model.

{phang}
{opt symmetric} in case the dyadic relationship is symmetric ({it:Y_ij=Y_ji}) dataset need not to contain the full matrix.
If {opt symmteric} is specified, {cmd:ngreg} will assume only the triangular half is present and will complete matrix itself.


{title:Examples}



{title:Author}



{title:References}

{phang}Fafchamps M. and F. Gubert.(2006) The Formation of Risk Sharing Networks


{title:Also see}

{psee}
Online: {helpb regress} {helpb logit}{p_end}
